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of the following areas is an asset: fluid dynamics, droplet impact, multiphase flow, heat transfer, phase change, high-speed imaging, vacuum systems, optical diagnostics, or surface science. Experience
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measurements and/or Computational Fluid Dynamics (CFD) simulations. Specifically, you will assess where simplified assumptions in the model fall short. You will then train a machine learning model (such as PySR
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Science, Physics, Mathematics or Computer Science. You have a solid background in computational fluid dynamics (CFD) and be proficient in programming (e.g., Python, Fortran, or C++) and visualization tools
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of Experimental Aerodynamics, Computational Fluid Dynamics and Flow Control. The group has a specific expertise in the field of advanced experimental and computational techniques for the analysis of aerodynamic
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. Job description The Aerodynamics group is composed of 12 scientific staff and hosts the Chairs of Experimental Aerodynamics, Computational Fluid Dynamics and Flow Control. The group has a specific
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succesful candidate has the following qualifications: An PhD degree in either applied physics, chemical engineering, mechanical engineering or a similar field Profound knowledge of thermodynamics and/or fluid
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throughout their evolution. Our vision combines ideas from differential geometry, numerical analysis, scientific computing, dynamical systems, and applied mathematics to develop new mathematical frameworks